scholarly journals A New Epigenetic Model to Stratify Glioma Patients According to Their Immunosuppressive State

Cells ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 576
Author(s):  
Maurizio Polano ◽  
Emanuele Fabbiani ◽  
Eva Adreuzzi ◽  
Federica Di Cintio ◽  
Luca Bedon ◽  
...  
Keyword(s):  
The Cancer Genome Atlas ◽  
Classification Model ◽  
Low Grade ◽  
Machine Learning Classification ◽  
Immune State ◽  
Out Of Sample ◽  
Cancer Genome Atlas ◽  
The Central Nervous System ◽  
Neural Network Classifiers ◽  
Definition Of

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Furthermore, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state.

scholarly journals CeRNA Network Analysis Representing Characteristics of Different Tumor Environments Based on 1p/19q Codeletion in Oligodendrogliomas

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2543
Author(s):  
Ju Won Ahn ◽  
YoungJoon Park ◽  
Su Jung Kang ◽  
So Jung Hwang ◽  
Kyung Gi Cho ◽  
...  
Keyword(s):  
Network Analysis ◽  
Underlying Mechanism ◽  
The Cancer Genome Atlas ◽  
Potassium Ion Channels ◽  
Low Grade ◽  
Tumor Microenvironments ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
The Central Nervous System ◽  
Composition Changes

Oligodendroglioma (OD) is a subtype of glioma occurring in the central nervous system. The 1p/19q codeletion is a prognostic marker of OD with an isocitrate dehydrogenase (IDH) mutation and is associated with a clinically favorable overall survival (OS); however, the exact underlying mechanism remains unclear. Long non-coding RNAs (lncRNAs) have recently been suggested to regulate carcinogenesis and prognosis in cancer patients. Here, we performed in silico analyses using low-grade gliomas from datasets obtained from The Cancer Genome Atlas to investigate the effects of ceRNA with 1p/19q codeletion on ODs. Thus, we selected modules of differentially expressed genes that were closely related to 1p/19q codeletion traits using weighted gene co-expression network analysis and constructed 16 coding RNA–miRNA–lncRNA networks. The ceRNA network participated in ion channel activity, insulin secretion, and collagen network and extracellular matrix (ECM) changes. In conclusion, ceRNAs with a 1p/19q codeletion can create different tumor microenvironments via potassium ion channels and ECM composition changes; furthermore, differences in OS may occur. Moreover, if extrapolated to gliomas, our results can provide insights into the consequences of identical gene expression, indicating the possibility of tracking different biological processes in different subtypes of glioma.

TNFα signalling predicts poor prognosis of patients with endometrial cancer

2020 ◽  
Vol 41 (8) ◽  
pp. 1065-1073
Author(s):  
Verena Wieser ◽  
Samira Abdel Azim ◽  
Susanne Sprung ◽  
Katharina Knoll ◽  
Johanna Kögl ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Clinical Outcome ◽  
The Cancer Genome Atlas ◽  
Western World ◽  
Low Grade ◽  
Necrosis Factor Alpha ◽  
Cancer Genome Atlas ◽  
Factor Alpha ◽  
The Impact

Abstract Endometrial cancer (EC) is the most common gynaecologic tumour in the Western world. Previous studies have implicated an imbalance of oestrogens and progestogens in the development of most ECs, while the role of low-grade tissue inflammation remains largely unexplored. We investigated the impact of tumour necrosis factor alpha (TNFα), a central mediator of inflammation and spermatogenesis-associated protein 2 (SPATA2), a regulator of TNF receptor signalling, on clinical outcomes in EC. We evaluated TNFA and SPATA2 transcript levels in 239 EC patients and 25 non-malignant control tissues. Findings were validated in a cohort of 332 EC patients from The Cancer Genome Atlas (TCGA). Expression of TNFA and SPATA2 was increased in EC when compared with control tissues (P < 0.001). TNFA expression correlated with SPATA2 expression in non-malignant (P = 0.003, rS = 0.568) and EC tissue (P = 0.005, rS = 0.179). High TNFA and SPATA2 expression were associated with poor recurrence-free survival (RFS; P = 0.049 and P = 0.018) and disease-specific (P = 0.034 and P = 0.002) survival. Increased SPATA2 expression was also associated with decreased overall survival (OS; P = 0.013). In multivariate analysis, both TNFA and SPATA2 were predictors of clinical outcome. The impact of SPATA2 on RFS and OS could be validated in the TCGA cohort. Our study demonstrates that ECs exhibit a TNF signature which predicts clinical outcome. These findings indicate that TNF signalling modulates the course of EC, which could be therapeutically utilized in the future.

scholarly journals Molecular Determinants of Prognosis and Evolution in Diffuse-Lower Grade Astrocytomas

2020 ◽  
Author(s):  
Mehul Kumar ◽  
J Gregory Cairncross ◽  
Michael D Blough ◽  
Pinaki Bose
Keyword(s):  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Lower Grade ◽  
Mutational Status ◽  
Molecular Determinants ◽  
Pdgf Signaling ◽  
Evolutionary Trajectories ◽  
Cancer Genome Atlas ◽  
Natural Histories ◽  
Worse Prognosis

ABSTRACTLow grade astrocytomas (LGAs) are classified based on the mutational status of the isocitrate dehydrogenase (IDH) gene. While IDH wild-type (WT) LGAs evolve rapidly to glioblastoma, mutant tumors generally have a more indolent course. To identify potential drivers of the differential progression of LGAs, we analyzed transcriptomes from The Cancer Genome Atlas. Compared to mutant LGAs, platelet-derived growth factor (PDGF) signaling is enriched in WT cases, and PDGFA is the top overexpressed gene in the pathway. Putative mechanisms for differential PDGFA expression included copy number gains of chromosome 7 in WT cases and methylation of the PDGFA promoter in mutant LGAs. Additionally, we found that high PDGFA expression is associated with aneuploidy, immunosuppressive features, and worse prognosis, and that WT LGAs use multiple means to inactivate the p53 pathway to progress to GBM. Our work highlights the contribution of PDGF gene family towards the unique behaviour of LGAs.STATEMENT OF SIGNIFICANCEThis study of gene expression in LGAs suggests that differential regulation of the PDGF pathway may underlie the different natural histories of IDH WT and IDH mutant LGAs including divergent evolutionary trajectories to GBM. This insight may inspire new therapeutic strategies to suppress the transformation of LGAs to higher-grade cancers.

scholarly journals A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme

2021 ◽  
Vol 11 ◽  
Author(s):  
Ming Gao ◽  
Xinzhuang Wang ◽  
Dayong Han ◽  
Enzhou Lu ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Immune Cell ◽  
Area Under The Curve ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Non Coding Rna ◽  
Cancer Genome Atlas ◽  
The Central Nervous System

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system. As biomedicine advances, the researcher has found the development of GBM is closely related to immunity. In this study, we evaluated the GBM tumor immunoreactivity and defined the Immune-High (IH) and Immune-Low (IL) immunophenotypes using transcriptome data from 144 tumors profiled by The Cancer Genome Atlas (TCGA) project based on the single-sample gene set enrichment analysis (ssGSEA) of five immune expression signatures (IFN-γ response, macrophages, lymphocyte infiltration, TGF-β response, and wound healing). Next, we identified six immunophenotype-related long non-coding RNA biomarkers (im-lncRNAs, USP30-AS1, HCP5, PSMB8-AS1, AL133264.2, LINC01684, and LINC01506) by employing a machine learning computational framework combining minimum redundancy maximum relevance algorithm (mRMR) and random forest model. Moreover, the expression level of identified im-lncRNAs was converted into an im-lncScore using the normalized principal component analysis. The im-lncScore showed a promising performance for distinguishing the GBM immunophenotypes with an area under the curve (AUC) of 0.928. Furthermore, the im-lncRNAs were also closely associated with the levels of tumor immune cell infiltration in GBM. In summary, the im-lncRNA signature had important clinical implications for tumor immunophenotyping and guiding immunotherapy in glioblastoma patients in future.

scholarly journals Bioinformatics Analysis of Differentially Expressed Genes and miRNAs in Low-Grade Gliomas

2020 ◽  
Vol 19 ◽  
pp. 117693512096969
Author(s):  
Mohammed Amine Bendahou ◽  
Azeddine Ibrahimi ◽  
Mahjouba Boutarbouch
Keyword(s):  
Large Scale ◽  
Regulation Of Gene Expression ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Molecular Precursors ◽  
Low Grade Gliomas ◽  
Micro Rnas ◽  
Limma Package ◽  
Cancer Genome Atlas ◽  
Primary Intracranial Tumor

Low-grade glioma is the most common type of primary intracranial tumor. In the last 3 years, new observations of molecular precursors in adults with gliomas have led to a modification in the histopathologic classification of these brain tumors. Among the biomarkers that have been highlighted, we have the micro RNAs (miRNAs) which play a crucial role in the regulation of gene expression and the long noncoding RNAs (lncRNAs) controlling various cellular and metabolic pathways. In our study, large-scale data on sequenced RNA and miRNAs from 516 patients were obtained from the Cancer Genome Atlas database by the TCGAbiolinks package. We identified the differential expression of miRNAs and genes using the Limma package and then we used the ClusterProfiler package for annotations of the biological pathways of the expressed genes, the survival package to estimate the survival analysis, and the GDCRNATools package to determine miRNAs-genes and miRNAs-lncRNAs interactions. We obtained a significant correlation between the miRNAs identified and the overall survival of the patients (log-rank P < .05) and we have theoretically proposed a novel network of miRNAs involved in low-grade gliomas, specifically astrocytomas and oligodendrogliomas, which combine both genes and lncRNAs.

scholarly journals The Cancer Genome Atlas expression profiles of low-grade gliomas

2014 ◽  
Vol 36 (4) ◽  
pp. E23 ◽  
Author(s):  
David D. Gonda ◽  
Vincent J. Cheung ◽  
Karra A. Muller ◽  
Amit Goyal ◽  
Bob S. Carter ◽  
...  
Keyword(s):  
Cpg Island ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Low Grade ◽  
Cpg Island Methylator Phenotype ◽  
Low Grade Gliomas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Differentiating between low-grade gliomas (LGGs) of astrocytic and oligodendroglial origin remains a major challenge in neurooncology. Here the authors analyzed The Cancer Genome Atlas (TCGA) profiles of LGGs with the goal of identifying distinct molecular characteristics that would afford accurate and reliable discrimination of astrocytic and oligodendroglial tumors. They found that 1) oligodendrogliomas are more likely to exhibit the glioma-CpG island methylator phenotype (G-CIMP), relative to low-grade astrocytomas; 2) relative to oligodendrogliomas, low-grade astrocytomas exhibit a higher expression of genes related to mitosis, replication, and inflammation; and 3) low-grade astrocytic tumors harbor microRNA profiles similar to those previously described for glioblastoma tumors. Orthogonal intersection of these molecular characteristics with existing molecular markers, such as IDH1 mutation, TP53 mutation, and 1p19q status, should facilitate accurate and reliable pathological diagnosis of LGGs.

scholarly journals Tumor mutational burden predicts survival in patients with low-grade gliomas expressing mutated IDH1

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Mahmoud S Alghamri ◽  
Rohit Thalla ◽  
Ruthvik P Avvari ◽  
Ali Dabaja ◽  
Ayman Taher ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Low Grade Gliomas ◽  
Mutational Burden ◽  
Gene Sets ◽  
Tumor Mutational Burden ◽  
Cancer Genome Atlas ◽  
Gene Ontologies

Abstract Background Gliomas are the most common primary brain tumors. High-Grade Gliomas have a median survival (MS) of 18 months, while Low-Grade Gliomas (LGGs) have an MS of approximately 7.3 years. Seventy-six percent of patients with LGG express mutated isocitrate dehydrogenase (mIDH) enzyme. Survival of these patients ranges from 1 to 15 years, and tumor mutational burden ranges from 0.28 to 3.85 somatic mutations/megabase per tumor. We tested the hypothesis that the tumor mutational burden would predict the survival of patients with tumors bearing mIDH. Methods We analyzed the effect of tumor mutational burden on patients’ survival using clinical and genomic data of 1199 glioma patients from The Cancer Genome Atlas and validated our results using the Glioma Longitudinal AnalySiS consortium. Results High tumor mutational burden negatively correlates with the survival of patients with LGG harboring mIDH (P = .005). This effect was significant for both Oligodendroglioma (LGG-mIDH-O; MS = 2379 vs 4459 days in high vs low, respectively; P = .005) and Astrocytoma (LGG-mIDH-A; MS = 2286 vs 4412 days in high vs low respectively; P = .005). There was no differential representation of frequently mutated genes (eg, TP53, ATRX, CIC, and FUBP) in either group. Gene set enrichment analysis revealed an enrichment in Gene Ontologies related to cell cycle, DNA-damage response in high versus low tumor mutational burden. Finally, we identified 6 gene sets that predict survival for LGG-mIDH-A and LGG-mIDH-O. Conclusions we demonstrate that tumor mutational burden is a powerful, robust, and clinically relevant prognostic factor of MS in mIDH patients.

scholarly journals miR-192 Is Overexpressed and Promotes Cell Proliferation in Prostate Cancer

2018 ◽  
Vol 28 (2) ◽  
pp. 124-132 ◽  
Author(s):  
Zhong-Jun  Chen ◽  
You-Ji Yan ◽  
Hao Shen ◽  
Jia-Jie Zhou ◽  
Guang-Hua Yang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cell Cycle Progression ◽  
Bioinformatic Analysis ◽  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Functional Roles ◽  
Normal Tissues ◽  
Cancer Genome Atlas

Objective: Prostate cancer (PCa) is one of the most prevalent types of cancer among men worldwide. The incidence of PCa is increasing in China. Therefore, there is an urgent need to identify novel diagnostic and prognostic markers for PCa to improve the treatment of the disease. Methods: The Cancer Genome Atlas (TCGA) and GEO database were used to analyze the expression of miR-192, and the relationship between miR-192 and the clinical features of patients with PCa. Cell cycle and cell proliferation assay were used to detect the functional roles of miR-192 in PCa. Bioinformatic analysis for miR-192–5p was performed using gene ontology and KEGG analysis. Results: By analyzing the dataset of TCGA, we found that miR-192 was overexpressed in PCa samples compared to normal tissues and was upregulated in high-grade PCa compared to low-grade PCa. We also observed that higher miR-192 expression was associated with a shorter biochemical recurrence-free survival time. Our results also demonstrated that miR-192 promoted PCa cell proliferation and cell cycle progression. Conclusion: These results suggest that miR-192 may be considered for use as a potential diagnostic and therapeutic target of PCa.

scholarly journals miR-10a and miR-204 as a Potential Prognostic Indicator in Low-Grade Gliomas

2017 ◽  
Vol 16 ◽  
pp. 117693511770287 ◽  
Author(s):  
Ju Cheol Son ◽  
Hyoung Oh Jeong ◽  
Deaui Park ◽  
Sang Gyoon No ◽  
Eun Kyeong Lee ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Target Genes ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Low Grade ◽  
Low Grade Gliomas ◽  
Clinical Biomarkers ◽  
Differentially Expressed Mirnas ◽  
Cancer Genome Atlas

This study aimed to identify and characterize microRNAs (miRNAs) that are related to radiosensitivity in low-grade gliomas (LGGs). The miRNA expression levels in radiosensitive and radioresistant LGGs were compared using The Cancer Genome Atlas database, and differentially expressed miRNAs were identified using the EBSeq package. The miRNA target genes were predicted using Web databases. Fifteen miRNAs were differentially expressed between the groups, with miR-10a and miR-204 being related to overall survival (OS) of patients with LGG. Patients with upregulated miR-10a expression had a higher mortality rate and shorter OS time, whereas patients with downregulated miR-204 expression had a lower mortality rate and longer OS time. Two genes, HSP90AA1 and CREB5, were targets for both miRNAs. Thus, this study suggests that expression of miR-10a and miR-204 is significantly related to both radiosensitivity and the survival of patients with LGG. These miRNAs could therefore act as clinical biomarkers for LGG prognosis and diagnosis.

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